Leveraging Fractured Well Performance With Economics Modeling to Increase Expected Value: A Tool For Strategic Decisions

2020 ◽  
Author(s):  
Omar Garza ◽  
Priscilla McLeroy
Keyword(s):  
Expected Value ◽  
Well Performance ◽  
Strategic Decisions ◽  
Fractured Well

scholarly journals Prediction of Hydraulic Fractured Well Performance Using Empirical Correlation and Machine Learning

2021 ◽  
Vol 44 (2) ◽  
pp. 131-145
Author(s):  
Kamal Hamzah ◽  
Amega Yasutra ◽  
Dedy Irawan
Keyword(s):  
Machine Learning ◽  
Hydraulic Fracturing ◽  
Petroleum Industry ◽  
Prediction Method ◽  
Empirical Correlation ◽  
Well Performance ◽  
Data Limitations ◽  
Medium Permeability ◽  
Water Cut ◽  
Fractured Well

Hydraulic fracturing has been established as one of production enhancement methods in the petroleum industry. This method is proven to increase productivity and reserves in low permeability reservoirs, while in medium permeability, it accelerates production without affecting well reserves. However, production result looks scattered and appears to have no direct correlation to individual parameters. It also tend to have a decreasing trend, hence the success ratio needs to be increased. Hydraulic fracturing in the South Sumatra area has been implemented since 2002 and there is plenty of data that can be analyzed to resolve the relationship between actual production with reservoir parameters and fracturing treatment. Empirical correlation approach and machine learning (ML) methods are both used to evaluate this relationship. Concept of Darcy's equation is utilized as basis for the empirical correlation on the actual data. The ML method is then applied to provide better predictions both for production rate and water cut. This method has also been developed to solve data limitations so that the prediction method can be used for all wells. Empirical correlation can gives an R2 of 0.67, while ML can gives a better R2 that is close to 0.80. Furthermore, this prediction method can be used for well candidate selection means.

Evaluating Fractured Well Performance Using Type Curves

1984 ◽  
Author(s):  
M.Y. Soliman ◽  
J.J. Venditto ◽  
G.L. Slusher
Keyword(s):  
Well Performance ◽  
Type Curves ◽  
Fractured Well

scholarly journals Optimization of Fractured Well Performance of Horizontal Gas Wells

2007 ◽  
Author(s):  
Fellipe Vieira Magalhaes ◽  
Ding Zhu ◽  
Shahram Amini ◽  
Peter P. Valko
Keyword(s):  
Well Performance ◽  
Gas Wells ◽  
Fractured Well

scholarly journals A production-based model for a fractured well in unconventional reservoirs

2020 ◽  
Author(s):  
Shaibu Mohammed ◽  
Prosper Anumah1 ◽  
Justice Sarkodie-kyeremeh ◽  
Emmanuel Acheaw
Keyword(s):  
Power Law ◽  
Numerical Models ◽  
Transient State ◽  
Production Performance ◽  
Unconventional Reservoirs ◽  
Well Performance ◽  
Type Curves ◽  
Stretched Exponential ◽  
Proposed Model ◽  
Fractured Well

Due to the depletion of conventional reservoirs and the high demand of energy, unconventional reservoirs will be relied on to supply the world’s energy for the foreseeable future. Unfortunately, modelling and analysis of these reservoirs have been very challenging because of their complex storage and flow mechanisms. Although analytical, semi-analytical and numerical models have been proposed, these models rely on simplifying assumptions and require several input parameters. In this paper, a production-based model is proposed to analyze and predict a fractured-well performance in unconventional reservoirs. The model assumes a power law with a stretched exponential cut-off. While the power-law term governs the transient-state period, the stretched exponential term, which is a superposition of exponential decays, governs the boundary-dominated flow period. As a result, the model is capable of matching both the transient state and boundary-dominated flow portions of the data. The model has been validated with a numerical data and applied to several field data; in addition, the model has been used to estimate P10, P50 and P90 values, as well as to develop P10, P50 and P90 type curves for the Barnett shale. These type curves will be useful for production forecasting of new wells in the field or analogue fields. Results of the model have been compared with existing models. The findings show that the proposed model yields relatively good reserve estimates, and predicts the future production performance of unconventional reservoirs not only during the transient-state period, but also the boundary-dominated flow period. The proposed model may contribute to the ongoing efforts to improve the analysis and forecasting of fractured-well performance in unconventional reservoirs.

Prediction of Hydraulic Fractured Well Performance Using Empirical Correlation and Machine Learning

2021 ◽  
Vol 44 (2) ◽  
pp. 141-152
Author(s):  
Kamal Hamzah ◽  
Amega Yasutra ◽  
Dedy Irawan
Keyword(s):  
Machine Learning ◽  
Hydraulic Fracturing ◽  
Petroleum Industry ◽  
Prediction Method ◽  
Empirical Correlation ◽  
Well Performance ◽  
Data Limitations ◽  
Medium Permeability ◽  
Water Cut ◽  
Fractured Well

Hydraulic fracturing has been established as one of production enhancement methods in the petroleum industry. This method is proven to increase productivity and reserves in low permeability reservoirs, while in medium permeability, it accelerates production without affecting well reserves. However, production result looks scattered and appears to have no direct correlation to individual parameters. It also tend to have a decreasing trend, hence the success ratio needs to be increased. Hydraulic fracturing in the South Sumatra area has been implemented since 2002 and there is plenty of data that can be analyzed to resolve the relationship between actual production with reservoir parameters and fracturing treatment. Empirical correlation approach and machine learning (ML) methods are both used to evaluate this relationship. Concept of Darcy's equation is utilized as basis for the empirical correlation on the actual data. The ML method is then applied to provide better predictions both for production rate and water cut. This method has also been developed to solve data limitations so that the prediction method can be used for all wells. Empirical correlation can gives an R2 of 0.67, while ML can gives a better R2 that is close to 0.80. Furthermore, this prediction method can be used for well candidate selection means.

Vertically Fractured Well Performance in Rectangular Drainage Area (Russian)

2006 ◽  
Author(s):  
V.V. Sabaev ◽  
D.S. Wolcott ◽  
J.M. Mach ◽  
D.V. Antipina ◽  
A.M. Haidar ◽  
...  
Keyword(s):  
Drainage Area ◽  
Well Performance ◽  
Fractured Well

Fractured-Well Performance Under Anomalous Diffusion

2013 ◽  
Vol 16 (03) ◽  
pp. 237-245 ◽  
Author(s):  
Rajagopal Raghavan ◽  
Chih Chen
Keyword(s):  
Anomalous Diffusion ◽  
Well Performance ◽  
Fractured Well
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